Organizations relying on mainframe and VMware environments often struggle with lengthy modernization timelines and limited resources. This blog illustrates how AWS Transform applies agentic AI to streamline modernization tasks that have traditionally required significant time and expertise. Read the blog to understand how this approach supports faster modernization outcomes, and contact CPACinc to discuss how AWS Transform fits your organization's long-term goals.
AWS Transform is a service offered by Amazon Web Services that utilizes agentic AI to facilitate the modernization of legacy workloads, specifically targeting mainframe and VMware systems. It automates complex tasks such as code analysis, refactoring, and migration planning, which helps organizations streamline their modernization efforts and reduce project timelines significantly.
How does AWS Transform address challenges in modernization?
AWS Transform addresses several challenges associated with legacy modernization, including high licensing costs, complex technical dependencies, and the need to manage team transitions. By automating assessment and transformation processes, it reduces the risks and complexities involved, enabling organizations to modernize with greater confidence and efficiency.
What are the phases of VMware workload modernization with AWS Transform?
The modernization of VMware workloads with AWS Transform is organized into four main phases: inventory discovery, wave planning, network conversion, and server migration. This structured approach allows organizations to effectively analyze their VMware environments and orchestrate migration waves, ensuring a smoother transition to cloud-based architectures.
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